The Experts below are selected from a list of 243 Experts worldwide ranked by ideXlab platform

Kayo Yoshida - One of the best experts on this subject based on the ideXlab platform.

  • its Applications. The Peak Sidelobe Level of Families of Binary Sequences
    2015
    Co-Authors: D. Mills, W. Sun, E. Müller, W. Willems, Y. Yang, Jonathan Jedwab, Kayo Yoshida
    Abstract:

    Z. Zhang, “On the cross correlation of sequences with the decimation factor d = (p + 1)=(p + 1) (p 1)=2, ” Applicable Alg. Eng.

  • the Peak Sidelobe Level of families of binary sequences
    International Symposium on Information Theory, 2006
    Co-Authors: Jonathan Jedwab, Kayo Yoshida
    Abstract:

    A numerical investigation is presented for the Peak Sidelobe Level (PSL) of Legendre sequences and maximal length shift register sequences (m-sequences). The PSL gives an alternative to the merit factor for measuring the collective smallness of the aperiodic autocorrelations of a binary sequence. The growth of the PSL of these infinite families of binary sequences is tested against the desired growth rate o(radic(n ln n)) for sequence length n. The claim that the PSL of m-sequences grows like O(radicn), which appears frequently in the radar literature, is concluded to be unproven and not currently supported by data. Notable similarities are uncovered between the PSL and merit factor behaviour under cyclic rotations of the sequences

  • the Peak Sidelobe Level of families of binary sequences
    IEEE Transactions on Information Theory, 2006
    Co-Authors: Jonathan Jedwab, Kayo Yoshida
    Abstract:

    A numerical investigation is presented for the Peak Sidelobe Level (PSL) of Legendre sequences, maximal length shift register sequences (m-sequences), and Rudin-Shapiro sequences. The PSL gives an alternative to the merit factor for measuring the collective smallness of the aperiodic autocorrelations of a binary sequence. The growth of the PSL of these infinite families of binary sequences is tested against the desired growth rate o(/spl radic/nlnn) for sequence length n. The claim that the PSL of m-sequences grows like O(/spl radic/n), which appears frequently in the radar literature, is concluded to be unproven and not currently supported by data. Notable similarities are uncovered between the PSL and merit factor behavior under cyclic rotations of the sequences.

Jonathan Jedwab - One of the best experts on this subject based on the ideXlab platform.

  • its Applications. The Peak Sidelobe Level of Families of Binary Sequences
    2015
    Co-Authors: D. Mills, W. Sun, E. Müller, W. Willems, Y. Yang, Jonathan Jedwab, Kayo Yoshida
    Abstract:

    Z. Zhang, “On the cross correlation of sequences with the decimation factor d = (p + 1)=(p + 1) (p 1)=2, ” Applicable Alg. Eng.

  • bounds on the growth rate of the Peak Sidelobe Level of binary sequences
    Advances in Mathematics of Communications, 2007
    Co-Authors: Denis Dmitriev, Jonathan Jedwab
    Abstract:

    The Peak Sidelobe Level (PSL) of a binary sequence is the largest absolute value of all its nontrivial aperiodic autocorrelations. A classical prob- lem of digital sequence design is to determine how slowly the PSL of a length n binary sequence can grow, as n becomes large. Moon and Moser showed in 1968 that the growth rate of the PSL of almost all length n binary sequences lies between order p nlogn and p n, but since then no theoretical improvement to these bounds has been found. We present the first numerical evidence on the tightness of these bounds, showing that the PSL of almost all binary sequences of length n appears to grow exactly like order p nlogn, and that the PSL of almost all m-sequences of length n appears to grow exactly like order p n. In the case of m-sequences, a key algorithmic insight reveals behaviour that was previously well beyond the range of computation.

  • the Peak Sidelobe Level of families of binary sequences
    International Symposium on Information Theory, 2006
    Co-Authors: Jonathan Jedwab, Kayo Yoshida
    Abstract:

    A numerical investigation is presented for the Peak Sidelobe Level (PSL) of Legendre sequences and maximal length shift register sequences (m-sequences). The PSL gives an alternative to the merit factor for measuring the collective smallness of the aperiodic autocorrelations of a binary sequence. The growth of the PSL of these infinite families of binary sequences is tested against the desired growth rate o(radic(n ln n)) for sequence length n. The claim that the PSL of m-sequences grows like O(radicn), which appears frequently in the radar literature, is concluded to be unproven and not currently supported by data. Notable similarities are uncovered between the PSL and merit factor behaviour under cyclic rotations of the sequences

  • the Peak Sidelobe Level of families of binary sequences
    IEEE Transactions on Information Theory, 2006
    Co-Authors: Jonathan Jedwab, Kayo Yoshida
    Abstract:

    A numerical investigation is presented for the Peak Sidelobe Level (PSL) of Legendre sequences, maximal length shift register sequences (m-sequences), and Rudin-Shapiro sequences. The PSL gives an alternative to the merit factor for measuring the collective smallness of the aperiodic autocorrelations of a binary sequence. The growth of the PSL of these infinite families of binary sequences is tested against the desired growth rate o(/spl radic/nlnn) for sequence length n. The claim that the PSL of m-sequences grows like O(/spl radic/n), which appears frequently in the radar literature, is concluded to be unproven and not currently supported by data. Notable similarities are uncovered between the PSL and merit factor behavior under cyclic rotations of the sequences.

Nikolay Nikolov - One of the best experts on this subject based on the ideXlab platform.

  • on the generation of long binary sequences with record breaking psl values
    arXiv: Signal Processing, 2021
    Co-Authors: Miroslav Dimitrov, Tsonka Baitcheva, Nikolay Nikolov
    Abstract:

    Binary sequences are widely used in various practical fields, such as telecommunications, radar technology, navigation, cryptography, measurement sciences, biology or industry. In this paper, a method to generate long binary sequences (LBS) with low Peak Sidelobe Level (PSL) value is proposed. Having an LBS with length $n$, both the time and memory complexities of the proposed algorithm are $\mathcal{O}(n)$. During our experiments, we repeatedly reach better PSL values than the currently known state of art constructions, such as Legendre sequences, with or without rotations, Rudin-Shapiro sequences or m-sequences, with or without rotations, by always reaching a record-breaking PSL values strictly less than $\sqrt{n}$. Furthermore, the efficiency and simplicity of the proposed method are particularly beneficial to the lightweightness of the implementation, which allowed us to reach record-breaking PSL values for less than a second.

  • on the generation of long binary sequences with record breaking psl values
    IEEE Signal Processing Letters, 2020
    Co-Authors: Miroslav Dimitrov, Tsonka Baitcheva, Nikolay Nikolov
    Abstract:

    Binary sequences are widely used in various practical fields, such as telecommunications, radar technology, navigation, cryptography, measurement sciences, biology or industry. In this letter, a method to generate long binary sequences (LBS) with low Peak Sidelobe Level (PSL) value is proposed. Having an LBS with length $n$ , both the time and memory complexities of the proposed algorithm are $\mathcal {O}(n)$ . During our experiments, we repeatedly reach better PSL values than the currently known state of art constructions, such as Legendre sequences, with or without rotations, Rudin-Shapiro sequences or m-sequences, with or without rotations, by always reaching a record-breaking PSL values strictly less than $\sqrt{n}$ . Furthermore, the efficiency and simplicity of the proposed method are particularly beneficial to the lightweightness of the implementation, which allowed us to reach record-breaking PSL values for less than a second.

Wei Cen - One of the best experts on this subject based on the ideXlab platform.

  • linear sparse array synthesis via convex optimization
    International Symposium on Circuits and Systems, 2010
    Co-Authors: Ling Cen, Wee Ser, Wei Cen
    Abstract:

    Due to the constraint on half-wavelength inter-element spacing of a uniformly spaced array, sparse arrays are usually designed to be non-uniformly spaced. Through proper design, unequally-spaced sparse arrays can have higher spatial resolution, lower Sidelobe and less number of sensors required in comparison with uniformly spaced arrays. However, the synthesis of a sparse array is a non-convex process as the array beampattern is an exponential or trigonometric function of sensor positions. In this paper, we propose a synthesis scheme, where the design of sparse arrays is formulated as a convex optimization problem. The array weights are optimized to achieve minimum Peak Sidelobe Level (PSL) as well as maximizing the sparsity of the array by optimizing an objective function that includes two terms, one measures the PSL and the other measures the sparsity of array. Sparse array is then obtained by removing those sensors with weights approximately equal to zero. The proposed design scheme eliminates the need of optimization according to sensor positions, which consequently solves the problem in non-convex optimization that cannot guarantee to find the optimum solution with reasonable computation time. Numerical studies show that it can be successfully applied to sparse array synthesis with low computational complexity. Moreover, lower PSL and higher resolution of mainlobe can be achieved in comparison with a uniformly spaced array.

  • linear sparse array synthesis with minimum number of sensors
    IEEE Transactions on Antennas and Propagation, 2010
    Co-Authors: Ling Cen, Wee Ser, Susanto Rahardja, Wei Cen
    Abstract:

    The number of sensors employed in an array affects the array performance, computational load, and cost. Consequently, the minimization of the number of sensors is of great importance in practice. However, relatively fewer research works have been reported on the later. In this paper, a novel optimization method is proposed to address this issue. In the proposed method, the improved genetic algorithm that has been presented at a conference recently, is used to optimize the weight coefficients and sensor positions of the array. Sensors that contribute the least to the array performance are then removed systematically until the smallest acceptable number of sensors is obtained. Specifically, this paper reports the study on the relationship between the Peak Sidelobe Level and the sensor weights, and uses the later to select the sensors to be removed. Through this approach, the desired beam pattern can be synthesized using the smallest number of sensors efficiently. Numerical results show that the proposed sensor removal method is able to achieve good Sidelobe suppression with a smaller number of sensors compared to other existing algorithms. The computational load required by our proposed approach is about one order less than that required by other existing algorithms too.

Bo Chen - One of the best experts on this subject based on the ideXlab platform.

  • knowledge based spatial temporal hierarchical mimo radar waveform design method for target detection in heterogeneous clutter zone
    IEEE Transactions on Signal Processing, 2015
    Co-Authors: Bo Jiu, Hongwei Liu, Xu Wang, Lei Zhang, Yinghua Wang, Bo Chen
    Abstract:

    Knowledge-based MIMO radar waveform design for target detection in heterogeneous clutter zone is addressed in this paper. In order to improve the detection probability efficiently, a new optimization cost function is developed via minimizing the output clutter Peak Level and Peak Sidelobe Level of the correlation function on the premise of maintaining the output target signal energy. With constant modulus constraint of transmit waveform, the new cost function is an NP-hard problem. To tackle this problem, a spatial-temporal hierarchical optimization approach is proposed that can decompose the original problem to two hierarchical subproblems approximately. On the foundation of convex programming and cyclic algorithm, the first subproblem, i.e., knowledge-based transmit beampattern design, can be solved effectively. Based on CVX programming and the bi-iterative method, the joint mainlobe synthesized signal and mismatched receiving filter optimization method is proposed to solve the second subproblem. Numerical results show the efficiency of the proposed method.

  • orthogonal genetic algorithm for planar thinned array designs
    International Journal of Antennas and Propagation, 2012
    Co-Authors: Li Zhang, Yongchang Jiao, Bo Chen
    Abstract:

    An orthogonal genetic algorithm (OGA) is applied to optimize the planar thinned array with a minimum Peak Sidelobe Level. The method is a genetic algorithm based on orthogonal design. A crossover operator formed by the orthogonal array and the factor analysis is employed to enhance the genetic algorithm for optimization. In order to evaluate the performance of the OGA, 20×10-element planar thinned arrays have been designed to minimize Peak Sidelobe Level. The optimization results by the OGA are better than the previously published results.